243 Aws Sagemaker Jobs - Page 6

Role Overview: We are looking for a highly experienced MLOps and ML Engineer to lead the design, deployment, and optimization of machine learning systems at scale. This role requires deep expertise in MLOps practices, CI/CD automation, and AWS SageMaker, with a strong foundation in machine learning engineering and cloud-native development. Key Responsibilities: Architect and implement robust MLOps pipelines for model development, deployment, monitoring, and governance. Lead the operationalization of ML models using AWS SageMaker and other AWS services. Build and maintain CI/CD pipelines for ML workflows using tools like GitHub Actions, Jenkins, or AWS CodePipeline. Automate model lifecycle management including retraining, versioning, and rollback. Collaborate with data scientists, ML engineers, and DevOps teams to ensure seamless integration and scalability. Monitor production models for performance, drift, and reliability. Establish best practices for reproducibility, security, and compliance in ML systems. Required Skills: 10+ years of experience in ML Engineering, MLOps, or related fields. Deep hands-on experience with AWS SageMaker, Lambda, S3, CloudWatch, and related AWS services. Strong programming skills in Python and experience with Docker, Kubernetes, and Terraform. Expertise in CI/CD tools and infrastructure-as-code. Familiarity with model monitoring tools (e.g., Evidently, Prometheus, Grafana). Solid understanding of ML algorithms, data pipelines, and production-grade systems. Preferred Qualifications: AWS Certified Machine Learning Specialty or DevOps Engineer certification. Experience with feature stores, model registries, and real-time inference systems. Leadership experience in cross-functional ML/AI teams. Primary Skills: MLOps, ML Engineering, AWS related services (SageMaker/S3/CloudWatch)

AI Opportunities with Soul AIs Expert Community!. Are you an MLOps Engineer ready to take your expertise to the next levelSoul AI (by Deccan AI) is building an elite network of AI professionals, connecting top-tier talent with cutting-edge projects. Why Join. Above market-standard compensation. Contract-based or freelance opportunities (2"“12 months). Work with industry leaders solving real AI challenges. Flexible work locations- Remote | Onsite | Hyderabad/Bangalore. Your Role:. Architect and optimize ML infrastructure with Kubeflow, MLflow, SageMaker Pipelines. Build CI/CD pipelines (GitHub Actions, Jenkins, GitLab CI/CD). Automate ML workflows (feature engineering, retraining, deployment). Scale ML models with Docker, Kubernetes, Airflow. Ensure model observability, security, and cost optimization in cloud (AWS/GCP/Azure). Must-Have Skills: . Proficiency in Python, TensorFlow, PyTorch, CI/CD pipelines. Hands-on experience with cloud ML platforms (AWS SageMaker, GCP Vertex AI, Azure ML). Expertise in monitoring tools (MLflow, Prometheus, Grafana). Knowledge of distributed data processing (Spark, Kafka). (BonusExperience in A/B testing, canary deployments, serverless ML). Next Steps:. Register on Soul AIs website. Get shortlisted & complete screening rounds. Join our Expert Community and get matched with top AI projects. Dont just find a job. Build your future in AI with Soul AI!.

AI Opportunities with Soul AIs Expert Community!. Are you an MLOps Engineer ready to take your expertise to the next levelSoul AI (by Deccan AI) is building an elite network of AI professionals, connecting top-tier talent with cutting-edge projects. Why Join. Above market-standard compensation. Contract-based or freelance opportunities (2"“12 months). Work with industry leaders solving real AI challenges. Flexible work locations- Remote | Onsite | Hyderabad/Bangalore. Your Role:. Architect and optimize ML infrastructure with Kubeflow, MLflow, SageMaker Pipelines. Build CI/CD pipelines (GitHub Actions, Jenkins, GitLab CI/CD). Automate ML workflows (feature engineering, retraining, deployment). Scale ML models with Docker, Kubernetes, Airflow. Ensure model observability, security, and cost optimization in cloud (AWS/GCP/Azure). Must-Have Skills: . Proficiency in Python, TensorFlow, PyTorch, CI/CD pipelines. Hands-on experience with cloud ML platforms (AWS SageMaker, GCP Vertex AI, Azure ML). Expertise in monitoring tools (MLflow, Prometheus, Grafana). Knowledge of distributed data processing (Spark, Kafka). (BonusExperience in A/B testing, canary deployments, serverless ML). Next Steps:. Register on Soul AIs website. Get shortlisted & complete screening rounds. Join our Expert Community and get matched with top AI projects. Dont just find a job. Build your future in AI with Soul AI!.

AI Opportunities with Soul AIs Expert Community!. Are you an MLOps Engineer ready to take your expertise to the next levelSoul AI (by Deccan AI) is building an elite network of AI professionals, connecting top-tier talent with cutting-edge projects. Why Join. Above market-standard compensation. Contract-based or freelance opportunities (2"“12 months). Work with industry leaders solving real AI challenges. Flexible work locations- Remote | Onsite | Hyderabad/Bangalore. Your Role:. Architect and optimize ML infrastructure with Kubeflow, MLflow, SageMaker Pipelines. Build CI/CD pipelines (GitHub Actions, Jenkins, GitLab CI/CD). Automate ML workflows (feature engineering, retraining, deployment). Scale ML models with Docker, Kubernetes, Airflow. Ensure model observability, security, and cost optimization in cloud (AWS/GCP/Azure). Must-Have Skills: . Proficiency in Python, TensorFlow, PyTorch, CI/CD pipelines. Hands-on experience with cloud ML platforms (AWS SageMaker, GCP Vertex AI, Azure ML). Expertise in monitoring tools (MLflow, Prometheus, Grafana). Knowledge of distributed data processing (Spark, Kafka). (BonusExperience in A/B testing, canary deployments, serverless ML). Next Steps:. Register on Soul AIs website. Get shortlisted & complete screening rounds. Join our Expert Community and get matched with top AI projects. Dont just find a job. Build your future in AI with Soul AI!.

AI Opportunities with Soul AIs Expert Community!. Are you an MLOps Engineer ready to take your expertise to the next levelSoul AI (by Deccan AI) is building an elite network of AI professionals, connecting top-tier talent with cutting-edge projects. Why Join. Above market-standard compensation. Contract-based or freelance opportunities (2"“12 months). Work with industry leaders solving real AI challenges. Flexible work locations- Remote | Onsite | Hyderabad/Bangalore. Your Role:. Architect and optimize ML infrastructure with Kubeflow, MLflow, SageMaker Pipelines. Build CI/CD pipelines (GitHub Actions, Jenkins, GitLab CI/CD). Automate ML workflows (feature engineering, retraining, deployment). Scale ML models with Docker, Kubernetes, Airflow. Ensure model observability, security, and cost optimization in cloud (AWS/GCP/Azure). Must-Have Skills: . Proficiency in Python, TensorFlow, PyTorch, CI/CD pipelines. Hands-on experience with cloud ML platforms (AWS SageMaker, GCP Vertex AI, Azure ML). Expertise in monitoring tools (MLflow, Prometheus, Grafana). Knowledge of distributed data processing (Spark, Kafka). (BonusExperience in A/B testing, canary deployments, serverless ML). Next Steps:. Register on Soul AIs website. Get shortlisted & complete screening rounds. Join our Expert Community and get matched with top AI projects. Dont just find a job. Build your future in AI with Soul AI!.

Job Title: Senior AI Cloud Operations Engineer Seniority: 4-5 OffShore Profile Summary: We're looking for a Senior AI Cloud Operations Engineer to start building a new for AI Cloud Operations team, starting with this strategic position. We are searching for an experienced Senior AI Cloud Operations Engineer with deep expertise in AI technologies to lead our cloud-based AI infrastructure management. This role is integral to ensuring our AI systems scalability, reliability, and performance, enabling us to deliver cutting-edge solutions. The ideal candidate will have a robust understanding of machine learning frameworks, cloud services architecture, and operations management. Key Responsibilities: Cloud Architecture Design: Design, architect, and manage scalable cloud infrastructure tailored for AI workloads, leveraging platforms like AWS, Azure, or Google Cloud. System Monitoring and Optimization: Implement comprehensive monitoring solutions to ensure high availability and swift performance, utilizing tools like Prometheus, Grafana, or CloudWatch. Collaboration and Model Deployment: Work closely with data scientists to operationalize AI models, ensuring seamless integration with existing systems and workflows. Familiarity with tools such as MLflow or TensorFlow Serving can be beneficial. Automation and Orchestration: Develop automated deployment pipelines using orchestration tools like Kubernetes and Terraform to streamline operations and reduce manual interventions. Security and Compliance: Ensure that all cloud operations adhere to security best practices and compliance standards, including data privacy regulations like GDPR or HIPAA. Documentation and Reporting: Create and maintain detailed documentation of cloud configurations, procedures, and operational metrics to foster transparency and continuous improvement. Performance Tuning: Conduct regular performance assessments and implement strategies to optimize cloud resource utilization and reduce costs without compromising system effectiveness. Issue Resolution: Rapidly identify, diagnose, and resolve technical issues, minimizing downtime and ensuring maximum uptime. Qualifications: Educational Background: Bachelor's degree in Computer Science, Engineering, or a related field. Master's degree preferred. Professional Experience: 5+ years of extensive experience in cloud operations, particularly within AI environments. Demonstrated expertise in deploying and managing complex AI systems in cloud settings . Technical Expertise: Deep knowledge of cloud platforms (AWS, Azure, Google Cloud) including their AI-specific services such as AWS SageMaker or Google AI Platform. AI/ML Proficiency: In-depth understanding of AI/ML frameworks and libraries such as TensorFlow, PyTorch, Scikit-learn, along with experience in ML model lifecycle management. Infrastructure as Code: Proficiency in infrastructure-as-code tools such as Terraform and AWS CloudFormation to automate and manage cloud deployment processes. Containerization and Microservices: Expertise in managing containerized applications using Docker and orchestrating services with Kubernetes. Soft Skills: Strong analytical, problem-solving, and communication skills, with the ability to work effectively both independently and in collaboration with cross-functional teams. Preferred Qualifications Advanced certifications in cloud services, such as AWS Certified Solutions Architect or Google Cloud Professional Data Engineer. Experience in advanced AI techniques such as deep learning or reinforcement learning. Knowledge of emerging AI technologies and trends to drive innovation within existing infrastructure. List of Used Tools: Cloud Provider: Azure, AWS or Google. Performance & monitor: Prometheus, Grafana, or CloudWatch. Collaboration and Model Deployment: MLflow or TensorFlow Serving Automation and Orchestration: Kubernetes and Terraform Security and Compliance: Data privacy regulations like GDPR or HIPAA. Job Title: Senior AI Cloud Operations Engineer Seniority: 4-5 OffShore Profile Summary: We're looking for a Senior AI Cloud Operations Engineer to start building a new for AI Cloud Operations team, starting with this strategic position. We are searching for an experienced Senior AI Cloud Operations Engineer with deep expertise in AI technologies to lead our cloud-based AI infrastructure management. This role is integral to ensuring our AI systems scalability, reliability, and performance, enabling us to deliver cutting-edge solutions. The ideal candidate will have a robust understanding of machine learning frameworks, cloud services architecture, and operations management. Key Responsibilities: Cloud Architecture Design: Design, architect, and manage scalable cloud infrastructure tailored for AI workloads, leveraging platforms like AWS, Azure, or Google Cloud. System Monitoring and Optimization: Implement comprehensive monitoring solutions to ensure high availability and swift performance, utilizing tools like Prometheus, Grafana, or CloudWatch. Collaboration and Model Deployment: Work closely with data scientists to operationalize AI models, ensuring seamless integration with existing systems and workflows. Familiarity with tools such as MLflow or TensorFlow Serving can be beneficial. Automation and Orchestration: Develop automated deployment pipelines using orchestration tools like Kubernetes and Terraform to streamline operations and reduce manual interventions. Security and Compliance: Ensure that all cloud operations adhere to security best practices and compliance standards, including data privacy regulations like GDPR or HIPAA. Documentation and Reporting: Create and maintain detailed documentation of cloud configurations, procedures, and operational metrics to foster transparency and continuous improvement. Performance Tuning: Conduct regular performance assessments and implement strategies to optimize cloud resource utilization and reduce costs without compromising system effectiveness. Issue Resolution: Rapidly identify, diagnose, and resolve technical issues, minimizing downtime and ensuring maximum uptime. Qualifications: Educational Background: Bachelor's degree in Computer Science, Engineering, or a related field. Master's degree preferred. Professional Experience: 5+ years of extensive experience in cloud operations, particularly within AI environments. Demonstrated expertise in deploying and managing complex AI systems in cloud settings . Technical Expertise: Deep knowledge of cloud platforms (AWS, Azure, Google Cloud) including their AI-specific services such as AWS SageMaker or Google AI Platform. AI/ML Proficiency: In-depth understanding of AI/ML frameworks and libraries such as TensorFlow, PyTorch, Scikit-learn, along with experience in ML model lifecycle management. Infrastructure as Code: Proficiency in infrastructure-as-code tools such as Terraform and AWS CloudFormation to automate and manage cloud deployment processes. Containerization and Microservices: Expertise in managing containerized applications using Docker and orchestrating services with Kubernetes. Soft Skills: Strong analytical, problem-solving, and communication skills, with the ability to work effectively both independently and in collaboration with cross-functional teams. Preferred Qualifications Advanced certifications in cloud services, such as AWS Certified Solutions Architect or Google Cloud Professional Data Engineer. Experience in advanced AI techniques such as deep learning or reinforcement learning. Knowledge of emerging AI technologies and trends to drive innovation within existing infrastructure. List of Used Tools: Cloud Provider: Azure, AWS or Google. Performance & monitor: Prometheus, Grafana, or CloudWatch. Collaboration and Model Deployment: MLflow or TensorFlow Serving Automation and Orchestration: Kubernetes and Terraform Security and Compliance: Data privacy regulations like GDPR or HIPAA.

RESPONSIBILITIES: Develop, productionize, and deploy scalable, resilient software solutions for operationalizing AI & ML. Deploy Machine Learning (ML) models and Large Language Models (LLM) securely and efficiently, both in the cloud and on-premises, using state of the art platforms, tools, and techniques. Provide effective model observability, monitoring, and metrics by instrumenting logging, dashboards, alerts, etc. In collaboration with Data Engineers, design and build pipelines for extraction, transformation, and loading of data from a variety of data sources for AI & ML models as well as RAG architectures for LLMs. Enable Data Scientists to work more efficiently by providing tools for experiment tracking and test automation. Ensure scalability of built solutions by developing and running rigorous load tests. Facilitate integration of AI & ML capabilities into user experience by building APIs, UIs, etc. Stay current on new developments in AI & ML frameworks, tools, techniques, and architectures available for solution development, both private and open source. Coach data scientists and data engineers on software development best practices to write scalable, maintainable, well-designed code. Agile Project Work Work in cross-functional agile teams of highly skilled software/machine learning engineers, data scientists, DevOps engineers, designers, product managers, technical delivery teams, and others to continuously innovate AI and MLOps solutions. Act as a positive champion for broader organization to develop stronger understanding of software design patterns that deliver scalable, maintainable, well-designed analytics solutions. Advocate for security and responsibility best practices and tools. Acts as an expert on complex technical topics that require cross-functional consultation. Perform other duties as required. QUALIFICATIONS: Experience applying continuous integration/continuous delivery best practices, including Version Control, Trunk Based Development, Release Management, and Test-Driven Development Experience with popular MLOps tools (e.g., Domino Data Labs, Dataiku, mlflow, AzureML, Sagemaker), and frameworks (e.g.: TensorFlow, Keras, Theano, PyTorch, Caffe, etc.) Experience with LLM platforms (OpenAI, Bedrock, NVAIE) and frameworks (LangChain, LangFuse, vLLM, etc.) Experience in programming languages common to data science such as Python, SQL, etc. Understanding of LLMs, and supporting concepts (tokenization, guardrails, chunking, Retrieval Augmented Generation, etc.). Knowledge of ML lifecycle (wrangling data, model selection, model training, modeling validation and deployment at scale) and experience working with data scientists Familiar with at least one major cloud provider (Azure, AWS, GCP), including resource provisioning, connectivity, security, autoscaling, IaC. Familiar with cloud data warehousing solutions such as Snowflake, Fabric, etc. Experience with Agile and DevOps software development principles/methodologies and working on teams focused on delivering business value. Experience influencing and building mindshare convincingly with any audience. Confident and experienced in public speaking. Ability to communicate complex ideas in a concise way. Fluent with popular diagraming and presentation software. Demonstrated experience in teaching and/or mentoring professionals.

Role & responsibilities Machine Learning, Data Science, Model Customization [4+ Years] Exp with performing above on cloud services e.g AWS SageMaker and other tools AI/ Gen AI skills: [1 or 2 years] MCP, RAG pipelines, A2A, Agentic / AI Agents Framework Auto Gen, Lang graph, Lang chain, codeless workflow builders etc. Preferred candidate profile Build working POC and prototypes rapidly. Build / integrate AI driven solutions to solve the identified opportunities, challenges. Lead cross functional teams in identifying and prioritizing key business areas in which AI solutions can result benefits. Proposals to executives and business leaders on broad range of technology, strategy and standard, governance for AI. Work on functional design, process design (flow mapping), prototyping, testing, defining support model in collaboration with Engineering and business leaders. Articulate and document the solutions architecture and lessons learned for each exploration and accelerated incubation. Relevant IT Experience: - 10+ years of relevant IT experience in given technology

Role Purpose: As a Software Development Engineer in the MLOps team, you will help design and build scalable, high-performance infrastructure for deploying and serving machine learning models. Role Value: As an SDE III, youll architect robust ML infrastructure to support efficient model deployment, serving, and optimization. You'll develop CI/CD pipelines for ML workflows, utilize compiler and hardware-based optimizations to improve inference performance, and drive cost efficiency. You will also influence development processes and tooling for continuous improvement. Key Responsibilities: Design and optimize model serving infrastructure with a focus on low latency and cost efficiency Build scalable inference pipelines across different hardware acceleration options Implement monitoring and observability solutions for ML systems Collaborate with ML Engineers to define best practices for deployment Develop enterprise-grade, cost-efficient ML solutions Work closely with MLEs, QA, and DevOps teams in a distributed environment Evaluate new technologies and contribute to system architecture decisions Drive continuous improvements in ML infrastructure Required Experience & Skills: 5+ years of experience in software engineering using Python Hands-on experience with ML frameworks (especially PyTorch) Experience optimizing ML models using hardware accelerators (e.g., AWS Neuron, ONNX, TensorRT) Familiarity with AWS ML services and hardware-accelerated compute (e.g., SageMaker, Inferentia, Trainium) Proven ability to build and maintain serverless architectures on AWS Strong understanding of event-driven patterns (SQS/SNS) and caching strategies Proficiency with Docker and container orchestration tools Solid grasp of RESTful API design and implementation Focus on secure, high-quality code with experience using static code analysis tools Strong problem-solving, algorithmic thinking, and communication skills Nice to Have: Experience with model compilation, quantization, and inference benchmarking Exposure to regulated environments with compliance-heavy requirements for cloud-based solutions Role & responsibilities Preferred candidate profile

Job Title: Industry & Function AI Decision Science Manager + S&C GN Management Level:07 - Manager Location: Primary Bengaluru, Secondary Gurugram Must-Have Skills: Consumer Goods & Services domain expertise , AI & ML, Proficiency in Python, R, PySpark, SQL , Experience in cloud platforms (Azure, AWS, GCP) , Expertise in Revenue Growth Management, Pricing Analytics, Promotion Analytics, PPA/Portfolio Optimization, Trade Investment Optimization. Good-to-Have Skills: Experience with Large Language Models (LLMs) like ChatGPT, Llama 2, or Claude 2 , Familiarity with optimization methods, advanced visualization tools (Power BI, Tableau), and Time Series Forecasting Job Summary : As a Decision Science Manager , you will lead the design and delivery of AI solutions in the Consumer Goods & Services domain. This role involves working closely with clients to provide advanced analytics and AI-driven strategies that deliver measurable business outcomes. Your expertise in analytics, problem-solving, and team leadership will help drive innovation and value for the organization. Roles & Responsibilities: Analyze extensive datasets and derive actionable insights for Consumer Goods data sources (e.g., Nielsen, IRI, EPOS, TPM). Evaluate AI and analytics maturity in the Consumer Goods sector and develop data-driven solutions. Design and implement AI-based strategies to deliver significant client benefits. Employ structured problem-solving methodologies to address complex business challenges. Lead data science initiatives, mentor team members, and contribute to thought leadership. Foster strong client relationships and act as a key liaison for project delivery. Build and deploy advanced analytics solutions using Accentures platforms and tools. Apply technical proficiency in Python, Pyspark, R, SQL, and cloud technologies for solution deployment. Develop compelling data-driven narratives for stakeholder engagement. Collaborate with internal teams to innovate, drive sales, and build new capabilities. Drive insights in critical Consumer Goods domains such as Revenue Growth Management Pricing Analytics and Pricing Optimization Promotion Analytics and Promotion Optimization SKU Rationalization/ Portfolio Optimization Price Pack Architecture Decomposition Models Time Series Forecasting Professional & Technical Skills: Proficiency in AI and analytics solutions (descriptive, diagnostic, predictive, prescriptive, generative). Expertise in delivering large scale projects/programs for Consumer Goods clients on Revenue Growth Management - Pricing Analytics, Promotion Analytics, Portfolio Optimization, etc. Deep and clear understanding of typical data sources used in RGM programs POS, Syndicated, Shipment, Finance, Promotion Calendar, etc. Strong programming skills in Python, R, PySpark, SQL, and experience with cloud platforms (Azure, AWS, GCP) and proficient in using services like Databricks and Sagemaker. Deep knowledge of traditional and advanced machine learning techniques, including deep learning. Experience with optimization techniques (linear, nonlinear, evolutionary methods). Familiarity with visualization tools like Power BI, Tableau. Experience with Large Language Models (LLMs) like ChatGPT, Llama 2. Certifications in Data Science or related fields. Additional Information: The ideal candidate has a strong educational background in data science and a proven track record in delivering impactful AI solutions in the Consumer Goods sector. This position offers opportunities to lead innovative projects and collaborate with global teams. Join Accenture to leverage cutting-edge technologies and deliver transformative business outcomes. About Our Company | AccentureQualification Experience: Minimum 7-9 years of experience in data science, particularly in the Consumer Goods sector Educational Qualification: Bachelors or Masters degree in Statistics, Economics, Mathematics, Computer Science, or MBA (Data Science specialization preferred)

Skill required: Delivery - Advanced Analytics Designation: I&F Decision Sci Practitioner Specialist Qualifications: Master of Engineering/Masters in Business Economics Years of Experience: 7 to 11 years About Accenture Combining unmatched experience and specialized skills across more than 40 industries, we offer Strategy and Consulting, Technology and Operations services, and Accenture Song all powered by the worlds largest network of Advanced Technology and Intelligent Operations centers. Our 699,000 people deliver on the promise of technology and human ingenuity every day, serving clients in more than 120 countries. Visit us at www.accenture.com What would you do Data & AI You will be a core member of Accenture Operations global Data & AI group, an energetic, strategic, high-visibility and high-impact team, to innovate and transform the Accenture Operations business using machine learning, advanced analytics to support data-driven decisioning. What are we looking for Extensive experience in leading Data Science and Advanced Analytics delivery teams Strong statistical programming experience Python or working knowledge on cloud native platforms like AWS Sagemaker is preferred Azure/ GCP Experience working with large data sets and big data tools like AWS, SQL, PySpark, etc. Solid knowledge in at least more than two of the following Supervised and Unsupervised Learning, Classification, Regression, Clustering, Neural Networks, Ensemble Modelling (random forest, boosted tree, etc) Experience in working with Pricing models is a plus Experience in atleast one of these business domains:Energy, CPG, Retail, Marketing Analytics, Customer Analytics, Digital Marketing, eCommerce, Health, Supply Chain Extensive experience in client engagement and business development Ability to work in a global collaborative team environment Quick Learner and Independently deliver results. Qualifications:Masters / Ph.D. Computer science, Engineering, Statistics, Mathematics, Economics or related disciplines. Roles and Responsibilities: Building data science models to uncover deeper insights, predict future outcomes, and optimize business processes for clients. Utilizing advanced statistical and machine learning techniques to develop models that can assist in decision-making and strategic planning. Refining and improving data science models based on feedback, new data, and evolving business needs. Data Scientists in Operations follow multiple approaches for project execution from adapting existing assets to Operations use cases, exploring third-party and open-source solutions for speed to execution and for specific use cases to engaging in fundamental research to develop novel solutions. Data Scientists are expected to collaborate with other data scientists, subject matter experts, sales, and delivery teams from Accenture locations around the globe to deliver strategic advanced machine learning / data-AI solutions from design to deployment. Qualification Master of Engineering,Masters in Business Economics

Skill required: Delivery - Advanced Analytics Designation: I&F Decision Sci Practitioner Assoc Mgr Qualifications: Master of Engineering/Masters in Business Economics Years of Experience: 10 to 14 years About Accenture Combining unmatched experience and specialized skills across more than 40 industries, we offer Strategy and Consulting, Technology and Operations services, and Accenture Song all powered by the worlds largest network of Advanced Technology and Intelligent Operations centers. Our 699,000 people deliver on the promise of technology and human ingenuity every day, serving clients in more than 120 countries. Visit us at www.accenture.com What would you do Data & AI You will be a core member of Accenture Operations global Data & AI group, an energetic, strategic, high-visibility and high-impact team, to innovate and transform the Accenture Operations business using machine learning, advanced analytics to support data-driven decisioning. What are we looking for Extensive experience in leading Data Science and Advanced Analytics delivery teams Strong statistical programming experience Python or working knowledge on cloud native platforms like AWS Sagemaker is preferred Azure/ GCP Experience working with large data sets and big data tools like AWS, SQL, PySpark, etc. Solid knowledge in at least more than two of the following Supervised and Unsupervised Learning, Classification, Regression, Clustering, Neural Networks, Ensemble Modelling (random forest, boosted tree, etc) Experience in working with Pricing models is a plus Experience in atleast one of these business domains:Energy, CPG, Retail, Marketing Analytics, Customer Analytics, Digital Marketing, eCommerce, Health, Supply Chain Extensive experience in client engagement and business development Ability to work in a global collaborative team environment Quick Learner and Independently deliver results. Qualifications:Masters / Ph.D. Computer science, Engineering, Statistics, Mathematics, Economics or related disciplines. Roles and Responsibilities: Leading team of data scientists to build and deploy data science models to uncover deeper insights, predict future outcomes, and optimize business processes for clients. Refining and improving data science models based on feedback, new data, and evolving business needs. Analyze available data to identify opportunities for enhancing brand equity, improving retail margins, achieving profitable growth, and expanding market share for clients. Data Scientists in Operations follow multiple approaches for project execution from adapting existing assets to Operations use cases, exploring third-party and open-source solutions for speed to execution and for specific use cases to engaging in fundamental research to develop novel solutions. Data Scientists are expected to collaborate with other data scientists, subject matter experts, sales, and delivery teams from Accenture locations around the globe to deliver strategic advanced machine learning / data-AI solutions from design to deployment. Qualification Master of Engineering,Masters in Business Economics

Skill required: Delivery - Advanced Analytics Designation: I&F Decision Sci Practitioner Sr Analyst Qualifications: Any Graduation Years of Experience: 5 - 8 Years About Accenture Combining unmatched experience and specialized skills across more than 40 industries, we offer Strategy and Consulting, Technology and Operations services, and Accenture Song all powered by the worlds largest network of Advanced Technology and Intelligent Operations centers. Our 699,000 people deliver on the promise of technology and human ingenuity every day, serving clients in more than 120 countries. Visit us at www.accenture.com What would you do Data & AI You will be a core member of Accenture Operations global Data & AI group, an energetic, strategic, high-visibility and high-impact team, to innovate and transform the Accenture Operations business using machine learning, advanced analytics to support data-driven decisioning. What are we looking for Extensive experience in leading Data Science and Advanced Analytics delivery teams Strong statistical programming experience Python or working knowledge on cloud native platforms like AWS Sagemaker is preferred Azure/ GCP Experience working with large data sets and big data tools like AWS, SQL, PySpark, etc. Solid knowledge in at least more than two of the following Supervised and Unsupervised Learning, Classification, Regression, Clustering, Neural Networks, Ensemble Modelling (random forest, boosted tree, etc) Experience in working with Pricing models is a plus Experience in atleast one of these business domainsEnergy, CPG, Retail, Marketing Analytics, Customer Analytics, Digital Marketing, eCommerce, Health, Supply Chain Extensive experience in client engagement and business development Ability to work in a global collaborative team environment Quick Learner and Independently deliver results. QualificationsMasters / Ph.D. Computer science, Engineering, Statistics, Mathematics, Economics or related disciplines. Roles and Responsibilities: Extensive experience in leading Data Science and Advanced Analytics delivery teams Strong statistical programming experience Python or working knowledge on cloud native platforms like AWS Sagemaker is preferred Azure/ GCP Experience working with large data sets and big data tools like AWS, SQL, PySpark, etc. Solid knowledge in at least more than two of the following Supervised and Unsupervised Learning, Classification, Regression, Clustering, Neural Networks, Ensemble Modelling (random forest, boosted tree, etc) Experience in working with Pricing models is a plus Experience in atleast one of these business domainsEnergy, CPG, Retail, Marketing Analytics, Customer Analytics, Digital Marketing, eCommerce, Health, Supply Chain Extensive experience in client engagement and business development Ability to work in a global collaborative team environment Quick Learner and Independently deliver results. QualificationsMasters / Ph.D. Computer science, Engineering, Statistics, Mathematics, Economics or related disciplines. Qualification Any Graduation

We are looking for a top-notch Senior Software Engineer who is passionate about writing clean, scalable, and secure code. If you take pride in building sustainable applications that meet customer needs and thrive in a collaborative, agile environment, this role is for you. You’ll work with experienced engineers across the enterprise and gain exposure to a variety of automation and cloud technologies. As a Python developer, you will contribute to complex assignments involving cloud-native architectures, automation pipelines, serverless computing, and object-oriented programming. Technical Skills: Proficiency in Python and cloud platforms (AWS, Azure) Experience with MLFlow, Kubernetes, Terraform, AWS SageMaker, Lambda, Step Functions Familiarity with configuration management tools (Terraform, Ansible, CloudFormation) Experience with CI/CD pipelines (e.g., Jenkins, Groovy scripts) Containerization and orchestration (Docker, Kubernetes, ECS, ECR) Understanding of serverless architecture and cloud-native application design Knowledge of infrastructure as code (IaC), IaaS, PaaS, and SaaS models Exposure to AI/ML technologies and model management is a plus Strong verbal and written communication skills Qualifications: Bachelor’s degree in Computer Science, Information Systems, or a related field 4+ years of experience in architecting, designing, and implementing cloud solutions on AWS and/or Azure Proven experience with both relational and non-relational database systems Experience leading data architecture or cloud transformation initiatives Strong troubleshooting and analytical skills Relevant certifications in AWS or Azure preferred Roles and Responsibilities Analyze and translate business requirements into scalable and resilient designs Own and continuously improve parts of the application in an agile environment Develop high-quality, maintainable products using best engineering practices Collaborate with other developers and share design philosophies across the team Work in cross-functional teams including DevOps, Data, UX, and QA Build and manage fully automated build/test/deployment environments Ensure high availability and provide rapid response to production issues Contribute to the design of useful, usable, and desirable products Adapt to new programming languages, platforms, and frameworks as needed

Dear Candidate, We are seeking a Machine Learning Engineer to develop predictive models and deploy them into production. Ideal for professionals passionate about AI and data science. Key Responsibilities: Develop and train machine learning models Preprocess and analyze large datasets Deploy models using scalable infrastructure Collaborate with product teams to integrate ML solutions Required Skills & Qualifications: Strong knowledge of Python and ML libraries (scikit-learn, TensorFlow, PyTorch) Experience with data preprocessing and feature engineering Familiarity with model deployment techniques Bonus: Experience with cloud ML services (AWS SageMaker, Google AI Platform) Soft Skills: Strong troubleshooting and problem-solving skills. Ability to work independently and in a team. Excellent communication and documentation skills. Note: If interested, please share your updated resume and preferred time for a discussion. If shortlisted, our HR team will contact you. Kandi Srinivasa Delivery Manager Integra Technologies

*****GenAI DevOps Engineer AWS Bedrock***** *****Pune Hinjewadi***** *****Immediate Joiners Preferred***** *****Minimum 4 Days WFO***** Job Description: We are seeking a highly experienced GenAI DevOps Engineer to join our dynamic team in Pune. The ideal candidate will have a strong background in building, deploying, and optimizing Generative AI applications on AWS Bedrock, along with expertise in DevOps practices. You will be responsible for automating infrastructure, managing CI/CD pipelines, and ensuring high performance and reliability of AI models. Key Responsibilities: Design, develop, and deploy Generative AI applications leveraging AWS Bedrock and SageMaker. Automate infrastructure provisioning and deployment processes. Build and maintain robust CI/CD pipelines using CodePipeline and CodeBuild. Monitor application and model performance using CloudWatch, Prometheus, and Grafana. Optimize AI models for performance, scalability, and cost-efficiency. Work with RAG (Retrieval-Augmented Generation) tools such as LangChain, Haystack, and LlamaIndex for building advanced AI solutions. Collaborate with data scientists and developers to streamline model deployment and monitoring. Required Skills: Extensive hands-on experience with AWS Bedrock and SageMaker. Strong expertise in CI/CD tools: CodePipeline, CodeBuild. Proficiency with monitoring tools: CloudWatch, Prometheus, Grafana. Experience with RAG frameworks like LangChain, Haystack, and LlamaIndex. Solid understanding of DevOps best practices and automation. Ability to troubleshoot and optimize AI deployment pipelines. Excellent problem-solving and communication skills. Preferred Skills: Knowledge of containerization (Docker, Kubernetes). Familiarity with scripting languages (Python, Bash). Experience with cloud security best practices. Understanding of machine learning lifecycle management. Mandatory Skills: AWS Bedrock and SageMaker expertise. CI/CD pipeline automation. Monitoring and performance optimization. RAG-based application development.

Job Title: AWS Data Engineer Role Overview: We are seeking a skilled AWS Data Engineer to join our dynamic team. The ideal candidate will have a strong background in data engineering, with a focus on building and maintaining scalable data pipelines and infrastructure using AWS services. Key Responsibilities: Design and Implement Data Pipelines: Develop and maintain scalable data pipelines using AWS Glue, Lambda, and other AWS services. Data Storage and Management: Manage data lakes on AWS S3, ensuring efficient data storage and retrieval. ETL Processes: Automate ETL (Extract, Transform, Load) processes using AWS Step Functions and Apache Airflow. Collaboration: Work closely with data scientists to optimize machine learning models on AWS SageMaker. Data Security: Ensure data security and compliance with AWS IAM (Identity and Access Management) and KMS (Key Management Service) policies. Performance Tuning: Optimize performance of data processing and storage solutions. Qualifications: Educational Background: Bachelor's degree in computer science, Information Technology, or a related field. Experience: Proven experience as a Data Engineer, with a focus on AWS services. Technical Skills: Proficiency in AWS services such as Glue, Lambda, S3, Redshift, RDS (Postgres, MySql). Strong programming skills in Python, SQL, and other relevant languages. Problem-Solving: Strong analytical and problem-solving skills, with the ability to work in a fast-paced environment. Communication: Excellent communication and teamwork skills. Preferred Qualifications: Certifications: AWS Certified Data Analytics - Specialty or AWS Certified Data Engineer

Looking for a Sr MLOps Engineer with a strong background in Data Engineering, who aspire to be part of a Data Science & AI Operations function in R&D. This role involves applying advanced software engineering skills for the design, creation, management, and business use of large datasets, across a variety of Data/ML platforms. This is an ideal opportunity for individuals with a passion for applying DevOps Skills for AI/ML application development in the health-care sector. Preferred Requirements: M.S (preferred) or Ph.D. in Computer Science, Data Science, or related quantitative fields. Proven experience in applying advanced software engineering skills in Data Science platforms (Data/ML) Strong experience in using MLOps tools like AWS SageMaker, MLFlow and ML Frameworks like TensorFlow/PyTorch Hands-on Experience in CI/CD using tools Terraform/CloudFormation, Git, Containers Docker/Kubernetes, ECS/EKS, Helm Charts Strong knowledge and Hands-on Experience with Data Lakes in building Data Pipelines using Python, Apache Spark, Lambda, Step Functions, SQL, Glue ETL in AWS Working knowledge on Cloud Platforms & Infrastructure in AWS Programming and Scripting knowledge using Python (Must needed), CLI/SDK/CDK Ability to balance between Development and Research work on latest trends (GenAI Ops) Minimum Requirements: Master's Degree or Higher in Computer Science/Data Science The ability to fluently read, write, understand, and communicate in English. Relevant AWS Certifications related to ML/Data /Data (preferred) 3+ years of hands-on working experience in applying MLOps engineering for Data/AI with real-world problem solving in the medical device industry or equivalent industry experience is preferred.

As an Applied AI Engineer, you will work at the intersection of AI research and practical implementation. You will develop machine learning (ML) and deep learning (DL) models, integrate them into our SaaS platform, and optimize them for scalability, performance, and business impact. Key Responsibilities: Data Engineering & Feature Engineering: Work with structured and unstructured data to build high-quality datasets. Develop robust feature engineering pipelines to improve model accuracy. Implement data preprocessing and augmentation techniques. MLOps & AI Infrastructure: Build and maintain ML pipelines for continuous integration and deployment (CI/CD). Implement model monitoring, retraining, and performance tracking frameworks. Work with cloud platforms (AWS, GCP, Azure) for AI model deployment and scaling. AI Integration in SaaS Applications: Collaborate with software engineers to integrate AI models into customer-facing SaaS products. Develop APIs and microservices for seamless AI-powered functionalities. Optimize inference performance for real-time and batch processing scenarios. Collaboration & Research: Stay updated with the latest AI research and bring innovative solutions to production. Work closely with product managers, designers, and engineers to align AI capabilities with business goals. Participate in code reviews, knowledge sharing, and AI/ML best practices. Prompt Engineering: Design, develop, and refine AI-generated text prompts for various applications to ensure accuracy, engagement, and relevance Craft and optimize prompts that guide our AI systems to generate accurate, informative, and creative outputs Build accessible libraries of prompts, keywords, and syntax guidelines for optimal query results Develop robust evaluation frameworks to assess AI model performance and prompt effectiveness Test and analyze outputs by experimenting with different prompts and measuring against defined metrics Create dashboards and reporting tools to track AI performance across multiple dimensions Apply human judgment to identify gaps in AI-generated output and refine prompts accordingly Implement continuous improvement processes based on evaluation insights What Were Looking For: Experience: 5-6 years in AI/ML engineering, with hands-on experience in Generative AI, NLP and deploying AI solutions at scale. Technical Expertise: Strong background in machine learning, deep learning, and NLP. Proficiency in Python Help assess performance metrics, develop novel agent frameworks, create and oversee data workflows, and conduct extensive testing to deploy innovative capabilities. Ship with high intent and work with the team to improve your ability to iterate and ship AI-powered features over time. Experience with data processing tools (Pandas, NumPy, Spark, Dask). Familiarity with MLOps, CI/CD, and cloud platforms (AWS SageMaker, GCP Vertex AI, Azure ML). AI Deployment & Optimization: Experience with optimizing models for performance, interpretability, and real-time applications. Strong Problem-Solving Skills: Ability to translate business problems into AI-driven solutions. SaaS Experience (Preferred): Understanding of how AI enhances SaaS applications and workflows.

AWS AI/ML Expert with 5 to 6 years of hands on experience in designing, developing, and deploying artificial intelligence and machine learning solutions on the AWS cloud platform. The ideal candidate will have strong proficiency in AWS AI services

Ready to shape the future of work At Genpact, we don&rsquot just adapt to change&mdashwe drive it. AI and digital innovation are redefining industries, and we&rsquore leading the charge. Genpact&rsquos , our industry-first accelerator, is an example of how we&rsquore scaling advanced technology solutions to help global enterprises work smarter, grow faster, and transform at scale. From large-scale models to , our breakthrough solutions tackle companies most complex challenges. If you thrive in a fast-moving, tech-driven environment, love solving real-world problems, and want to be part of a team that&rsquos shaping the future, this is your moment. Genpact (NYSE: G) is an advanced technology services and solutions company that delivers lasting value for leading enterprises globally. Through our deep business knowledge, operational excellence, and cutting-edge solutions - we help companies across industries get ahead and stay ahead. Powered by curiosity, courage, and innovation, our teams implement data, technology, and AI to create tomorrow, today. Get to know us at and on , , , and Inviting applications for the role of Principal Consultant -Lead MLOps Engineer! In this role, you will define, implement and oversee the MLOps strategy for scalable, compliant, and cost-efficient deployment of AI/ GenAI models across the enterprise. This role combines deep DevOps knowledge, infrastructure architecture, and AI platform design to guide how teams build and ship ML models securely and reliably. You will establish governance, reuse, and automation frameworks for AI infrastructure, including Terraform-first cloud automation, multi-environment CI/CD, and observability pipelines. Responsibilities Architect secure, reusable, modular IaC frameworks across cloud and regions for MLOps Lead the development of CI/CD pipelines and standardize deployment frameworks. Design observability and monitoring systems for ML/ GenAI workloads. Collaborate with platform, data science, compliance and Enterprise Architecture teams to ensure scalable ML operations. Define enterprise-wide MLOps architecture and standards (build ? deploy ? monitor) Lead design of GenAI / LLMOps platform (Bedrock/OpenAI/Hugging Face + RAG stack) Integrate governance controls (approvals, drift detection, rollback strategies) Define model metadata standards, monitoring SLAs, and re-training workflows Influence tooling, hiring, and roadmap decisions for AI/ML delivery Be engaging in the design, development and maintenance of data pipelines for various AI use cases Required to actively contribution to key deliverables as part of an agile development team Qualifications we seek in you! Minimum Qualifications Good years of experience in DevOps or MLOps roles. Degree/qualification in Computer Science or a related field, or equivalent work experience Strong Python programming skills. Hands on experience in containerised deployment. Proficient with AWS (SageMaker, Lambda, ECR), Terraform, and Python. Demonstrated experience deploying multiple GenAI systems into production. Hands-on experience deploying 3-4 ML/ GenAI models in AWS. Deep understanding of ML model lifecycle: train ? test ? deploy ? monitor ? retrain. Experience in developing, testing, and deploying data pipelines using public cloud. Clear and effective communication skills to interact with team members, stakeholders and end users Knowledge of governance and compliance policies, standards, and procedures Exposure to RAG/LLM workloads and model deployment infrastructure. Experience in developing, testing, and deploying data pipelines Preferred Qualifications/ Skills Experience designing model governance frameworks and CI/CD pipelines. Knowledge of governance and compliance policies, standards, and procedures Advanced understanding of platform security, cost optimization, and ML observability. Why join Genpact Be a transformation leader - Work at the cutting edge of AI, automation, and digital innovation Make an impact - Drive change for global enterprises and solve business challenges that matter Accelerate your career - Get hands-on experience, mentorship, and continuous learning opportunities Work with the best - Join 140,000+ bold thinkers and problem-solvers who push boundaries every day Thrive in a values-driven culture - Our courage, curiosity, and incisiveness - built on a foundation of integrity and inclusion - allow your ideas to fuel progress Come join the tech shapers and growth makers at Genpact and take your career in the only direction that matters: Up. Let&rsquos build tomorrow together. Genpact is an Equal Opportunity Employer and considers applicants for all positions without regard to race, color , religion or belief, sex, age, national origin, citizenship status, marital status, military/veteran status, genetic information, sexual orientation, gender identity, physical or mental disability or any other characteristic protected by applicable laws. Genpact is committed to creating a dynamic work environment that values respect and integrity, customer focus, and innovation. Furthermore, please do note that Genpact does not charge fees to process job applications and applicants are not required to pay to participate in our hiring process in any other way. Examples of such scams include purchasing a %27starter kit,%27 paying to apply, or purchasing equipment or training.

As Lead ML Engineer , you'll lead the development of predictive models for demand forecasting, customer segmentation, and retail optimization, from feature engineering through deployment. As Lead ML Engineer, you'll lead the development of predictive models for demand forecasting, customer segmentation, and retail optimization, from feature engineering through deployment. Responsibilities: Build and deploy models for forecasting and optimization Perform time-series analysis, classification, and regression Monitor model performance and integrate feedback loops Use AWS SageMaker, MLflow, and explainability tools (e.g., SHAP or LIME)

Role : MLOps Engineer Location – PAN India Notice: Immediate to 60 days Key words -Skillset AWS SageMaker, Azure ML Studio, GCP Vertex AI PySpark, Azure Databricks MLFlow, KubeFlow, AirFlow, Github Actions, AWS CodePipeline Kubernetes, AKS, Terraform, Fast API Responsibilities Model Deployment, Model Monitoring, Model Retraining Deployment pipeline, Inference pipeline, Monitoring pipeline, Retraining pipeline Drift Detection, Data Drift, Model Drift Experiment Tracking MLOps Architecture REST API publishing Job Responsibilities: Research and implement MLOps tools, frameworks and platforms for our Data Science projects. Work on a backlog of activities to raise MLOps maturity in the organization. Proactively introduce a modern, agile and automated approach to Data Science. Conduct internal training and presentations about MLOps tools’ benefits and usage. Required experience and qualifications: Wide experience with Kubernetes. Experience in operationalization of Data Science projects (MLOps) using at least one of the popular frameworks or platforms (e.g. Kubeflow, AWS Sagemaker, Google AI Platform, Azure Machine Learning, DataRobot, DKube). Good understanding of ML and AI concepts. Hands-on experience in ML model development. Proficiency in Python used both for ML and automation tasks. Good knowledge of Bash and Unix command line toolkit. Experience in CI/CD/CT pipelines implementation. Experience with cloud platforms - preferably AWS - would be an advantage.

The Data Scientist organization within the Data and Analytics division is responsible for designing and implementing a unified data strategy that enables the efficient, secure, and governed use of data across the organization. We aim to create a trusted and customer-centric data ecosystem, built on a foundation of data quality, security, and openness, and guided by the Thomson Reuters Trust Principles. Our team is dedicated to developing innovative data solutions that drive business value while upholding the highest standards of data management and ethics. About the role: Work with low to minimum supervision to solve business problems using data and analytics. Work in multiple business domain areas including Customer Experience and Service, Operations, Finance, Sales and Marketing. Work with various business stakeholders, to understand and document requirements. Design an analytical framework to provide insights into a business problem. Explore and visualize multiple data sets to understand data available for problem solving. Build end to end data pipelines to handle and process data at scale. Build machine learning models and/or statistical solutions. Build predictive models. Use Natural Language Processing to extract insight from text. Design database models (if a data mart or operational data store is required to aggregate data for modeling). Design visualizations and build dashboards in Tableau and/or PowerBI Extract business insights from the data and models. Present results to stakeholders (and tell stories using data) using power point and/or dashboards. Work collaboratively with other team members. About you: Overall 3+ years' experience in technology roles. Must have a minimum of 1 years of experience working in the data science domain. Has used frameworks/libraries such as Scikit-learn, PyTorch, Keras, NLTK. Highly proficient in Python. Highly proficient in SQL. Experience with Tableau and/or PowerBI. Has worked with Amazon Web Services and Sagemaker. Ability to build data pipelines for data movement using tools such as Alteryx, GLUE, Informatica. Proficient in machine learning, statistical modelling, and data science techniques. Experience with one or more of the following types of business analytics applications: Predictive analytics for customer retention, cross sales and new customer acquisition. Pricing optimization models. Segmentation. Recommendation engines. Experience in one or more of the following business domains Customer Experience and Service. Finance. Operations. Good presentation skills and the ability to tell stories using data and PowerPoint/Dashboard Visualizations. Excellent organizational, analytical and problem-solving skills. Ability to communicate complex results in a simple and concise manner at all levels within the organization. Ability to excel in a fast-paced, startup-like environment. #LI-SS5 Whats in it For You Hybrid Work Model Weve adopted a flexible hybrid working environment (2-3 days a week in the office depending on the role) for our office-based roles while delivering a seamless experience that is digitally and physically connected. Flexibility & Work-Life Balance: Flex My Way is a set of supportive workplace policies designed to help manage personal and professional responsibilities, whether caring for family, giving back to the community, or finding time to refresh and reset. This builds upon our flexible work arrangements, including work from anywhere for up to 8 weeks per year, empowering employees to achieve a better work-life balance. Career Development and Growth: By fostering a culture of continuous learning and skill development, we prepare our talent to tackle tomorrows challenges and deliver real-world solutions. Our Grow My Way programming and skills-first approach ensures you have the tools and knowledge to grow, lead, and thrive in an AI-enabled future. Industry Competitive Benefits We offer comprehensive benefit plans to include flexible vacation, two company-wide Mental Health Days off, access to the Headspace app, retirement savings, tuition reimbursement, employee incentive programs, and resources for mental, physical, and financial wellbeing. Culture: Globally recognized, award-winning reputation for inclusion and belonging, flexibility, work-life balance, and more. We live by our valuesObsess over our Customers, Compete to Win, Challenge (Y)our Thinking, Act Fast / Learn Fast, and Stronger Together. Social Impact Make an impact in your community with our Social Impact Institute. We offer employees two paid volunteer days off annually and opportunities to get involved with pro-bono consulting projects and Environmental, Social, and Governance (ESG) initiatives. Making a Real-World Impact: We are one of the few companies globally that helps its customers pursue justice, truth, and transparency. Together, with the professionals and institutions we serve, we help uphold the rule of law, turn the wheels of commerce, catch bad actors, report the facts, and provide trusted, unbiased information to people all over the world. Thomson Reuters informs the way forward by bringing together the trusted content and technology that people and organizations need to make the right decisions. We serve professionals across legal, tax, accounting, compliance, government, and media. Our products combine highly specialized software and insights to empower professionals with the data, intelligence, and solutions needed to make informed decisions, and to help institutions in their pursuit of justice, truth, and transparency. Reuters, part of Thomson Reuters, is a world leading provider of trusted journalism and news. We are powered by the talents of 26,000 employees across more than 70 countries, where everyone has a chance to contribute and grow professionally in flexible work environments. At a time when objectivity, accuracy, fairness, and transparency are under attack, we consider it our duty to pursue them. Sound excitingJoin us and help shape the industries that move society forward. As a global business, we rely on the unique backgrounds, perspectives, and experiences of all employees to deliver on our business goals. To ensure we can do that, we seek talented, qualified employees in all our operations around the world regardless of race, color, sex/gender, including pregnancy, gender identity and expression, national origin, religion, sexual orientation, disability, age, marital status, citizen status, veteran status, or any other protected classification under applicable law. Thomson Reuters is proud to be an Equal Employment Opportunity Employer providing a drug-free workplace. We also make reasonable accommodations for qualified individuals with disabilities and for sincerely held religious beliefs in accordance with applicable law. More information on requesting an accommodation here. Learn more on how to protect yourself from fraudulent job postings here. More information about Thomson Reuters can be found on thomsonreuters.com.

About the Role: Grade Level (for internal use): 13 Location: Gurgaon, Hyderabad and Bangalore : We are seeking a highly skilled and visionary Agentic AI Architect to lead the strategic design, development, and scalable implementation of autonomous AI systems within our organization. This role demands an individual with deep expertise in cutting-edge AI architectures, a strong commitment to ethical AI practices, and a proven ability to drive innovation. The ideal candidate will architect intelligent, self-directed decision-making systems that integrate seamlessly with enterprise workflows and propel our operational efficiency forward. Key Responsibilities As an Agentic AI Architect, you will: AI Architecture and System Design: Architect and design robust, scalable, and autonomous AI systems that seamlessly integrate with enterprise workflows, cloud platforms, and advanced LLM frameworks. Define blueprints for APIs, agents, and pipelines to enable dynamic, context-aware AI decision-making. Strategic AI Leadership: Provide technical leadership and strategic direction for AI initiatives focused on agentic systems. Guide cross-functional teams of AI engineers, data scientists, and developers in the adoption and implementation of advanced AI architectures. Framework and Platform Expertise: Evaluate, recommend, and implement leading AI tools and frameworks, with a strong focus on autonomous AI solutions (e.g., multi-agent frameworks, self-optimizing systems, LLM-driven decision engines). Drive the selection and utilization of cloud platforms (AWS SageMaker preferred, Azure ML, Google Cloud Vertex AI) for scalable AI deployments. Customization and Optimization: Design strategies for optimizing autonomous AI models for domain-specific tasks (e.g., real-time analytics, adaptive automation). Define methodologies for fine-tuning LLMs, multi-agent frameworks, and feedback loops to align with overarching business goals and architectural principles. Innovation and Research Integration: Spearhead the integration of R&D initiatives into production architectures, advancing agentic AI capabilities. Evaluate and prototype emerging frameworks (e.g., Autogen, AutoGPT, LangChain), neuro-symbolic architectures, and self-improving AI systems for architectural viability. Documentation and Architectural Blueprinting: Develop comprehensive technical white papers, architectural diagrams, and best practices for autonomous AI system design and deployment. Serve as a thought leader, sharing architectural insights at conferences and contributing to open-source AI communities. System Validation and Resilience: Design and oversee rigorous architectural testing of AI agents, including stress testing, adversarial scenario simulations, and bias mitigation strategies, ensuring alignment with compliance, ethical and performance benchmarks for robust production systems. Stakeholder Collaboration & Advocacy: Collaborate with executives, product teams, and compliance officers to align AI architectural initiatives with strategic objectives. Advocate for AI-driven innovation and architectural best practices across the organization. Qualifications: Technical Expertise: 12+ years of progressive experience in AI/ML, with a strong track record as an AI Architect , ML Architect, or AI Solutions Lead. 7+ years specifically focused on designing and architecting autonomous/agentic AI systems (e.g., multi-agent frameworks, self-optimizing systems, or LLM-driven decision engines). Expertise in Python (mandatory) and familiarity with Node.js for architectural integrations. Extensive hands-on experience with autonomous AI tools and frameworks LangChain, Autogen, CrewAI, or architecting custom agentic frameworks. Proficiency in cloud platforms for AI architecture AWS SageMaker (most preferred), Azure ML, or Google Cloud Vertex AI, with a deep understanding of their AI service offerings. Demonstrable experience with MLOps pipelines (e.g., Kubeflow, MLflow) and designing scalable deployment strategies for AI agents in production environments. Leadership & Strategic Acumen: Proven track record of leading the architectural direction of AI/ML teams, managing complex AI projects, and mentoring senior technical staff. Strong understanding and practical application of AI governance frameworks (e.g., EU AI Act, NIST AI RMF) and advanced bias mitigation techniques within AI architectures. Exceptional ability to translate complex technical AI concepts into clear, concise architectural plans and strategies for non-technical stakeholders and executive leadership. Ability to envision and articulate a long-term strategy for AI within the business, aligning AI initiatives with business objectives and market trends. Foster collaboration across various practices, including product management, engineering, and marketing, to ensure cohesive implementation of AI strategies that meet business goals. Whats In It For You Our Purpose: Progress is not a self-starter. It requires a catalyst to be set in motion. Information, imagination, people, technologythe right combination can unlock possibility and change the world.Our world is in transition and getting more complex by the day. We push past expected observations and seek out new levels of understanding so that we can help companies, governments and individuals make an impact on tomorrow. At S&P Global we transform data into Essential Intelligence, pinpointing risks and opening possibilities. We Accelerate Progress. Our People: Our Values: Integrity, Discovery, Partnership At S&P Global, we focus on Powering Global Markets. Throughout our history, the world's leading organizations have relied on us for the Essential Intelligence they need to make confident decisions about the road ahead. We start with a foundation of integrity in all we do, bring a spirit of discovery to our work, and collaborate in close partnership with each other and our customers to achieve shared goals. Benefits: We take care of you, so you cantake care of business. We care about our people. Thats why we provide everything youand your careerneed to thrive at S&P Global. Health & WellnessHealth care coverage designed for the mind and body. Continuous LearningAccess a wealth of resources to grow your career and learn valuable new skills. Invest in Your FutureSecure your financial future through competitive pay, retirement planning, a continuing education program with a company-matched student loan contribution, and financial wellness programs. Family Friendly PerksIts not just about you. S&P Global has perks for your partners and little ones, too, with some best-in class benefits for families. Beyond the BasicsFrom retail discounts to referral incentive awardssmall perks can make a big difference. For more information on benefits by country visithttps://spgbenefits.com/benefit-summaries Global Hiring and Opportunity at S&P Global: At S&P Global, we are committed to fostering a connected andengaged workplace where all individuals have access to opportunities based on their skills, experience, and contributions. Our hiring practices emphasize fairness, transparency, and merit, ensuring that we attract and retain top talent. By valuing different perspectives and promoting a culture of respect and collaboration, we drive innovation and power global markets. ----------------------------------------------------------- Equal Opportunity Employer S&P Global is an equal opportunity employer and all qualified candidates will receive consideration for employment without regard to race/ethnicity, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, marital status, military veteran status, unemployment status, or any other status protected by law. Only electronic job submissions will be considered for employment. If you need an accommodation during the application process due to a disability, please send an email to EEO.Compliance@spglobal.com and your request will be forwarded to the appropriate person. US Candidates Only The EEO is the Law Poster http://www.dol.gov/ofccp/regs/compliance/posters/pdf/eeopost.pdf describes discrimination protections under federal law. Pay Transparency Nondiscrimination Provision - https://www.dol.gov/sites/dolgov/files/ofccp/pdf/pay-transp_%20English_formattedESQA508c.pdf ----------------------------------------------------------- 10 - Officials or Managers (EEO-2 Job Categories-United States of America), IFTECH103.2 - Middle Management Tier II (EEO Job Group), SWP Priority Ratings - (Strategic Workforce Planning)